Building phenotypic maps based on neuronal activity and transcriptional profiles in human cell models of syndromic forms of ASD

  • Awarded: 2019
  • Award Type: Pilot
  • Award #: 610264

Genetic analyses of large cohorts of individuals with autism spectrum disorder (ASD) have enabled the identification of numerous de novo and inherited rare DNA variants linked to ASD. Gene ontology analysis of the affected genes has revealed an enrichment of genes involved in synaptic processes and in transcription regulation through modulation of chromatin structure. Despite this considerable progress in elucidating the genetic architecture of ASD, a major gap exists between the genetic findings and deciphering the cellular or molecular pathobiology of ASD. In particular, there remains a gap in our understanding of which gene changes have the most relevant functional consequences and whether or not those consequences overlap in different individuals.

Nael Nadif Kasri proposes that the interrogation of neuronal network activity using micro-electrode arrays (MEAs) offers a robust, efficient and physiologically relevant readout to probe for ASD phenotypic differences at the neuronal network level. Kasri’s laboratory plans to generate a cohort of induced pluripotent stem cell (iPSC) lines from individuals with syndromic ASD, including ADNP, ANKRD11, ARID1B, CHD8, EHMT1 and MED12. The focus is initially on these genetically defined subtypes of ASD because the underlying genes are involved in shared biological processes (i.e., chromatin remodeling), which offers unparalleled opportunities for understanding key molecular and cellular pathophysiological mechanisms underlying ASD. The iPSC lines will then be differentiated into neuronal networks on MEAs to allow Kasri’s team to build phenotypic maps based on comparisons of network activity. To allow further correlations between genotypes, cellular events and neuronal physiological function, Kasri’s group will also perform RNA-Seq on the iPSC lines to obtain transcriptional data.

Kasri hypothesizes that each subtype of ASD will have a definable characteristic network phenotype and that this information can be combined with information on transcriptional states to interrogate the cellular and molecular mechanisms underlying the disorder as well as to inform drug screening tests aimed at reversing such phenotypes.

Subscribe to our newsletter and receive SFARI funding announcements and news